code: def base_architecture(args):
      # default architecture
      rnn.base_architecture(args)
      args.char_rnn_units = getattr(args, "char_embed_dim", 128)
      args.char_rnn_units = getattr(args, "char_rnn_units", 256)
      args.char_rnn_layers = getattr(args, "char_rnn_layers", 1)
  
imports: import logging
  from ast import literal_eval
  import torch
  import torch.nn.functional
  from fairseq.models import FairseqEncoder, register_model, register_model_architecture
  from pytorch_translate import char_encoder, model_constants, rnn, utils, vocab_constants
  from pytorch_translate.common_layers import Embedding, VariableTracker
  from pytorch_translate.data.dictionary import TAGS
label_desc: Use image node_id 2 for calling a global function with example usage: base_architecture(args) without return types